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Fuzzy λ-algebra with some related concepts

AIP Conference Proceedings 2023年第1期2414卷

作者： Mohaimen Muhammed Abbood Ali Al-Fayadh Hassan H. Ebrahim 1Department of Mathematicssand Computer Applications College of Science Al-Nahraini University Baghdad Iraq 2Department off Mathematics College of Computer Science and Mathematics Tikrit University Tikrit Salahaddin Iraq

The objective in this paper is to give the concept of fuzzy λ–algebra and study some of its structural properties. The relationships between fuzzy λ–algebra and other concepts like fuzzy α-σ-field, fuzzy β-σ-f...

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Geographical landmark recognition: Using CNN-Based approach to improve accuracy

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AIP Conference Proceedings 2022年第1期2576卷

作者： Kanishk Bansal Amar Singh 1Department of Computer Applications Lovely Professional University Phagwara Punjab India – 144411

Landmarks in a digital image are the visibly distinguishable objects that can be properly classified by human brain. In the field of computer vision, landmark recognition is an important topic since it involves the basic ability of machines to identify objects in an image. Training a machine to identify all the things in an image will involve training it on the most basic landmarks first. But landmark recognition is not an easy task to accomplish. The widely available datasets in the field of landmark recognition are not only very large to adversely impact the training, but they are also highly noisy and complex. Even the best of pictures clicked tend to contain a lot of noise in the processed data. To tackle the problem, we trained a Convolutional Neural Network (CNN) on a publicly available geographical landmarks dataset and found that both, training and test accuracies of CNNs (98% and 73% respectively),were higher than the classical machine learning techniques. Also, it was seen that overfitting of models was lesser in CNNs.

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Solution of fractional order random integro-differential equations using homotopy perturbation method

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AIP Conference Proceedings 2023年第1期2457卷

作者： Ali Adnan Abdul Sahib Fadhel S. Fadhel 1Department of Mathematics College of Education Mustansiriyah University Baghdad - Iraq 2Department of Mathematics and Computer Applications College of Science Al-Nahrain University Baghdad - Iraq

In this article, we shall introduce the homtopy perturbation method which was applied to obtain the approximate solution of the fractional order random integro-differential equations .The proof of the convergence of the obtained sequence of approximate solutions to the exact solution also introduced and presented. In addition, it may be noted that it is not easy to obtain the approximate solution using the homotopy perturbation method because of the existence of the Brownian motion or Winner process. Moreover, numerical results shows that our theoretical analysis are accurate and the homtopy perturbation method can be considered as a powerful method for solving fractional order random integro-differential equations.

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Optimizing thyroid stage classification system using enhanced data mining algorithms

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AIP Conference Proceedings 2022年第1期2516卷

作者： S. Parimala P. Senthil Vadivu 1Department of Computer Science SRM Institute of Science and Technology Chennai India 2Department of Computer Applications Hindustan College of Arts and Science Coimbatore India

In healthcare industry, the usage of automated diagnostic systems has become common in recent years. These systems offer several advantages during diagnosis. This system can minimize the operator-dependent nature inherent in medical imaging systems and can make the diagnostic process reproducible. And also helps to improve the accuracy of diagnosis. This effectively can work with features (like computational features and statistical features) that cannot be obtained through visual analysis or through intuitive examinations. In this work we have proposed the new algorithm called “Optimized Weighted KNNI algorithm” (OWKNNI). In this research paper we have sorted out the problem of missing value handling is used to detect the Thyroid Disease my enhancing the data mining algorithms to detect the type of thyroid diseases.

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Mature antibody immune response over SARS-CoV-2 as a pattern recognition with artificial immune system

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AIP Conference Proceedings 2022年第1期2481卷

作者： Manita Dhyani Dibyahash Bordoloi Anupriya Sharma Ghai 1Department of Computer Science and Engineering Graphic Era (Deemed to be) University Dehradun Uttarakhand India 248002 2Department of Computer Applications Graphic Era Hill University Dehradun India

A natural immune system has a remarkable ability to recognise self from nonself antigens in human body. The immune system has a natural ability to learn, recognise and respond accordingly to protect human body against viruses and diseases. B-cells produce detectable antibodies and immunoglobulins and are responsible for humoral antibody immunity (IgM, IgG). Memory cells play an important role in this entire reactive process. With the help of these memory cells, the immune system recognises and responds immediately to the second entry of infection.I propose a supervised machine learning method (Immunos -R) to give an approach to build an immune response model to get an accurate antibody immunological response to SARS-CoV-2 without doing in-vitro laboratory *** rate for antibody immunological response (B lymphocytes cells subset) is 96.0% at fourth split and lowest at 8th split 68.0%

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Kafka based LSTM model for streaming data prediction

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AIP Conference Proceedings 2022年第1期2444卷

作者： S. Geetha V. Kalaivani 1Department of Computer Applications Mepco Schlenk Engineering College Sivakasi Tamil Nadu India 2Department of Computer Science and Engineering National Engineering College Kovilpatti Tamil Nadu India

In the current technological world, the data is getting generated abundantly through various sources. The time dependent data generated through sensors is one among them. The most of the time dependent or time series data is streaming in real-time onfixed flow rates and sometimes, it will be on variation. When there is a change or no change in the flow of data, the existing state of the art prediction models provides low accuracy of prediction. Hence, it is proposed to have better accuracy of prediction on the streaming data with LSTM and Kafka Framework. The Kafka-LSTM model performed much better than the other conventional models. The models were evaluated using mean absolute error and root mean square error. The proposed method performs with better accuracy and reduced error rate than the other conventional models.

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A new approximate method for solving linear and non- linear differential equation systems

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AIP Conference Proceedings 2022年第1期2398卷

作者： Ahmed K. Al-Jaberi Mohammed S. Abdul-Wahab Rafid Habib Buti 1Department of Mathematics College of Education for Pure Sciences University of Basrah Basrah Iraq 2Department of Mathematics and Computer Applications College of Sciences University of Al-Muthanna Samawa Iraq

In this work, a new approximate method is proposed to enhance the accuracy and convergence of solutions for differential equations. This method uses the Taylors’ series in its derivation. The proposed method has used for solving different types of linear and nonlinear differential equation systems with the initial conditions. Four examples have presented to check the effectiveness, accuracy, and convergence of the method. The solutions of the proposed method also compared with those obtained by the Adomian decomposition method (ADM), and the Homotopy analysis method (HAM). The results of the proposed method outperformed the other methods in terms of accuracy and convergence.

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Development of a hybrid mapping scheme using matrix mapping and unicode in elliptic curve cryptography

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AIP Conference Proceedings 2022年第1期2520卷

作者： Sreekala M. Varghese Paul 1Department of Computer Applications Cochin University of Science & Technology Kochi & Department of Computer Science Vimala College Thrissur Kerala India 2Department of Information Technology Rajagiri School of Engineering and Technology Kakkanad Kochi Kerala India

We are now living in a digital universe. The wide world of technology with high level advancements has all started to gravitate towards our working lives, personal lives, and finances. This pervasive phenomenon, sadly, leaves us at more risk than ever to spiteful attacks, privacy stalking, fraud, and other such unpleasant things. Hence cyber security is such a crucial part of a stable and secure world. Elliptic curve cryptography is mainly used for encryption and decryption as an asymmetric encryption system in which, if you have to encrypt a message, first mapping the message by using an efficient mapping algorithm, they try to plot the message to a different point on the elliptic curve. Even though the arithmetic behind Elliptic curve cryptography is highly complex in nature, it is difficult to break. In this paper, we focus on various message mapping schemes in the cryptosystem of elliptic curves, the drawbacks of each strategy, and how sensitive to cryptanalysis they are. We are proposing a new mapping method that is unaffected by frequency analysis and other types of data analysis of crypto attacks in the later part of this paper.

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Use of agile software development method to manage academic resources

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AIP Conference Proceedings 2022年第1期2481卷

作者： Anupriya Sharma Ghai Divya Kapil Lakshita Sejwal Atika Gupta Swati Devliyal 1Department of Computer Applications Graphic Era Hill University Dehradun India 2Department of Computer Science & Engineering KCC Institute of Technology & Management Noida India 3Department of Computer Science and Engineering Graphic Era University Dehradun India

Agile is a method that moves quickly, lightly, and approachable in developing a software process. The primary goal of agile methodology is to produce high-quality software in a quicker time. It is using this methodology for developing the Academic Resource in a system provided by software for maintaining academic and financial records of data efficiently and conveniently. The administration of any academic association must make records of students registered and the staff of the university on paper and keep them safe, which is a tedious task due to the increase in manual work that reduced the utilization of the efficiency of staff. This paper describes a systematic approach to developing a user-friendly, flexible, and easy-to-maintain environment for academic resources using agile's extreme programming. The execution of the different tasks to develop the system is used to widen the horizons in Agile Methodologies step by step.

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Design of CMOS DC-DC converter for WSN/IOT applications

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AIP Conference Proceedings 2022年第1期2463卷

作者： Kumudham R. Sathish Kumar P. Rajendran V. V. Devi Gopi Krushna R. A. Sam Chelladurai S. 1Department of Electronics & Communication Engineering School of Engineering Vels Institute of Science Technology and Advanced Studies (VISTAS) Chennai India 2Department of Computer Applications Gurunanak College Chennai India

This paper proposed DC-DC converter with DT-CMOS Switch. The proposed circuit is designed for evaluating and compared with CMOS switch by both circuit simulation and device simulation. This DT-CMOS SWITCH reduces the output ripple and the conduction loss through a low on resistance. Therefore, proposed converter has excellent performance efficiency than converter with conventional CMOS switch. Simulations of eight phases phase locked loop circuit in 0.13 m standard CMOS technology reveal that the proposed charge pump circuit has given an input supply voltage of 1 V that has the output voltage of 6.7 V, which reaches the efficiency is 75%. Supplying a 5-mA load current maintains a power supply as well as 50 percent efficiency and a voltage output of above 5 volts. The proposed charge pump circuit employs body biasing and charge transfer switches to drastically reduce leakage while also increasing voltage. The result of simulation reveals that the proposed charge pump circuits perform better in terms of voltage pumping gain and power efficiency.

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